危重症患者ICU后疲劳发生风险预测模型的构建与验证OA
Development and validation of a predictive model for post-ICU fatigue risk in critically ill patients
目的 构建危重症患者ICU后疲劳的风险预测模型,并验证该模型的预测效果.方法 便利选取2024年1月至12月在贵州省某三级甲等医院综合ICU住院的236例危重症患者作为建模组,在患者转出 ICU 1个月时,采用疲劳严重程度量表对其进行电话随访,根据是否发生ICU后疲劳,将其分为疲劳组(155例)和非疲劳组(81例).采用单因素分析联合Logistic回归分析确定ICU后疲劳发生的独立危险因素,构建风险预测模型并绘制列线图.采用受试者操作特征曲线(ROC)、校准曲线、Hosmer-Lemeshow检验及决策曲线分析(DCA)评价该模型的准确度与有效性.选取2025年1月至3月同一所医院同一ICU住院治疗的114例危重症患者作为验证组,并采用ROC曲线和DCA进行模型验证.结果 建模集与验证集危重症患者ICU后疲劳发生率为65.68％、60.52％.年龄校正查尔森合并症指数(ACCI评分)、机械通气时间、ICU住院时间、急性生理和慢性健康状况评分(APACHE Ⅱ评分)、约束、贫血、中文版重症监护疼痛观察工具(CPOT评分)及生活自理能力评分(BI评分)是其独立危险因素(P＜0.05).建模集Hosmer-Lemeshow检验结果显示x2=6.511,P=0.590,ROC曲线下面积为0.936(95％CI:0.903～0.970),灵敏度为81.5％,特异度为92.6％.验证集Hosmer-Lemeshow检验结果显示x2=10.528,P=0.230,ROC曲线下面积为0.894(95％CI:0.828～0.960),该模型的灵敏度为91.7％,特异度为78.6％.结论 该风险预测模型的预测效果良好,可为医务人员评估危重症患者ICU后疲劳发生风险提供参考.
Objective To construct a risk prediction model for post-ICU fatigue in critically ill patients and vali-date its predictive efficacy.Methods A convenience sample of 236 critically ill patients admitted to the general ICU of a tertiary-level hospital in Guizhou Province from January to December 2024 was selected as the modeling cohort.Telephone follow-up using the Fatigue Severity Scale was conducted one month after ICU discharge.Pa-tients were categorized into a fatigue group(n=155)and a non-fatigue group(n=81)based on the occurrence of post-ICU fatigue.Univariate and multivariate logistic regression analyses identified independent risk factors for post-ICU fatigue.Univariate analysis combined with logistic regression was employed to identify independent risk factors for post-ICU fatigue.A risk prediction model was constructed and a nomogram was developed.The mod-el's accuracy and validity were evaluated using receiver operating characteristic(ROC)curves,calibration curves,Hosmer-Lemeshow tests,and decision curve analysis(DCA).A validation cohort of 114 critically ill patients admitted to the same ICU at the same hospital between January and March 2025 was selected.Model validation was performed using ROC curves and DCA.Results The incidence of post-ICU fatigue in critically ill patients was 65.68％in the training cohort and 60.52％in the validation cohort.Age-adjusted Charlson Comor-bidity Index(ACCI score),mechanical ventilation duration,ICU length of stay,Acute Physiology and Chronic Health Evaluation Ⅱ score(APACHE Ⅱ score),restraint use,anemia,Chinese version Critical Care Pain Ob-servation Tool(CPOT score),and Activities of Daily Living(ADL)score were identified as independent risk factors(P＜0.05).The Hosmer-Lemeshow test for the modeling set yielded x2=6.511,P=0.590,with an ar-ea under the ROC curve of 0.936(95％CI:0.903-0.970),sensitivity of 81.5％,and specificity of 92.6％.The Hosmer-Lemeshow test for the validation set yielded x2=10.528,P=0.230,with an AUC of 0.894(95％CI:0.828-0.960).The model demonstrated a sensitivity of 91.7％and specificity of 78.6％.Conclusion This risk prediction model demonstrates good predictive performance and can serve as a reference for healthcare providers in assessing the risk of post-ICU fatigue in critically ill patients.
辜甜田;陈俊希;王朝平;袁薇薇;王本金;胡汝均
遵义医科大学附属医院重症医学科,贵州遵义 563000||遵义医科大学护理学院,贵州遵义 563006遵义医科大学附属医院重症医学科,贵州遵义 563000||遵义医科大学护理学院,贵州遵义 563006遵义医科大学附属医院重症医学科,贵州遵义 563000||遵义医科大学护理学院,贵州遵义 563006遵义医科大学附属医院重症医学科,贵州遵义 563000||遵义医科大学护理学院,贵州遵义 563006遵义医科大学附属医院重症医学科,贵州遵义 563000||遵义医科大学护理学院,贵州遵义 563006遵义医科大学附属医院重症医学科,贵州遵义 563000||遵义医科大学护理学院,贵州遵义 563006
医药卫生
危重患者ICU后综合征疲劳危险因素风险预测模型列线图模型验证
critically ill patientspost-intensive care syndromefatiguerisk factorsrisk prediction modelnomogrammodel validation
《遵义医科大学学报》 2026 (4)
380-389,10
国家自然科学基金资助项目(NO:72464040).
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